The increase in bridge structure span and the complex stress characteristics directly affect the optimization of sensor placement,which in turn influences the data acquisition performance of the monitoring system.The ...The increase in bridge structure span and the complex stress characteristics directly affect the optimization of sensor placement,which in turn influences the data acquisition performance of the monitoring system.The key to the information acquisition of a bridge monitoring system is to obtain data that meets the health monitoring requirements of the bridge with a limited number of measurement points.To address this,a hybrid method based on multiple optimization criteria is proposed for optimal sensor placement(OSP).First,the minimum number of modes required for bridge monitoring is determined using the information entropy criterion(IE).Then,the number of measurement points is determined using a sequence method combined with the modal assurance criterion(MAC).Finally,the sensor placement is optimized using the generalized genetic algorithm(GGA)combined with double-structure encoding,and the optimization results are validated through finite element model analysis.The research results show that the hybrid method based on multiple optimization criteria can effectively determine the number of measurement points for bridge structures and optimize sensor placement,with a significant improvement in computational speed.展开更多
Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it...Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.展开更多
In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated....In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated. One of the key issues in designing is the system volume, which is determined by maximum interconnection distance(MID) between PEs. A novel 2 D genetic algorithm was presented in this paper at the first time, and used to solve the placement of twin butterfly multistage networks based on transmissive physical model. The experiment result shows that this algorithm case works better than other algorithm cases.展开更多
The fault current limiter(FCL)is an effective measure for improving system stability and suppressing short-circuit fault current.Because of space and economic costs,the optimum placement of FCLs is vital in industrial...The fault current limiter(FCL)is an effective measure for improving system stability and suppressing short-circuit fault current.Because of space and economic costs,the optimum placement of FCLs is vital in industrial applications.In this study,two objectives with the same dimensional measurement unit,namely,the total capital investment cost of FCLs and circuit breaker loss related to short-circuit currents,are considered.The circuit breaker loss model is developed based on the attenuation rule of the circuit breaker service life.The circuit breaker loss is used to quantify the current-limiting effect to avoid the problem of weight selection in a multi-objective problem.The IEEE 10-generator 39-bus system in New England is used to evaluate the performance of the proposed genetic algorithm(GA)method.Comparative and sensitivity analyses are performed.The results of the optimized plan are validated through simulations,indicating the significant potential of the GA for such optimization.展开更多
This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using c...This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.展开更多
With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data proc...With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.展开更多
This paper presents a study for finding a solution to the placement of territorial resources for multipurpose wireless services considering also the restrictions imposed by the orography of the territory itself. To so...This paper presents a study for finding a solution to the placement of territorial resources for multipurpose wireless services considering also the restrictions imposed by the orography of the territory itself. To solve this problem genetic algorithms are used to identify sites where to place the resources for the optimal coverage of a given area. The used algorithm has demonstrated to be able to find optimal solutions in a variety of considered situations.展开更多
Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to cont...Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to control action and a real coded genetic algorithm then proposed to produce a global optimum solution, and proves the feasibility and advantages of this algorithm with the example of a standard test function and a two collocated actuators/sensors cantilever, and comparing the results with those given in the literatures.展开更多
This paper presents the design of stability augmentation system (SAS) for the airship, which is robust with respect to parametric plant uncertainties. A robust pole placement approach is adopted in the design, which u...This paper presents the design of stability augmentation system (SAS) for the airship, which is robust with respect to parametric plant uncertainties. A robust pole placement approach is adopted in the design, which uses genetic algorithm (GA) as the optimization tool to derive the most robust solution of the state-feedback gain matrix K. The method can guarantee the resulting closed-loop poles to remain in a specified allocation region despite plant parameter uncertainty. Thus, the longitudinal stability of the airship is augmented by robustly assigning the closed-loop poles in a prescribed region of the left half s-plane.展开更多
A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calcu...A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes.The power rating of the ES is adjusted on the basis of the available active power at the bus.And in the optimization problem,it is expressed as the power ratio of the noncritical load(NCL)and critical load(CL).The implemented ES model is flexible,which can be used on any bus and any phase.The model determines the output voltage from the parameters and operating conditions at the point of common coupling(PCC).These conditions are integrated using the backward/forward sweep method(BFSM)and are updated during power flow calculations.The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BFSM-based genetic algorithm,which computes power flow and ES placement simultaneously.The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.展开更多
This paper presents a novel genetic algorithm for analog module placement based on a generalization of the two-dimensional bin packing problem. The genetic encoding and operators assure that all problem constraints ar...This paper presents a novel genetic algorithm for analog module placement based on a generalization of the two-dimensional bin packing problem. The genetic encoding and operators assure that all problem constraints are always satisfied. Thus the potential problems of adding penalty terms to the cost function are eliminated so that the search configuration space is drastically decreased. The dedicated cost function is based on the special requirements of analog integrated circuits. A fractional factorial experiment was conducted using an orthogonal array to study the algorithm parameters. A meta-GA was applied to determine the optimal parameter values. The algorithm was tested with several local benchmark circuits. The experimental results show that the algorithm has better performance than the simulated annealing approach with satisfactory results comparable to manual placement. This study demonstrates the effectiveness of the genetic algorithm in the analog module placement problem. The algorithm has been successfully used in a layout synthesis tool.展开更多
Most wind turbines within wind farms are set up to face a pre-determined wind direction.However,wind directions are intermittent in nature,leading to less electricity production capacity.This paper proposes an algorit...Most wind turbines within wind farms are set up to face a pre-determined wind direction.However,wind directions are intermittent in nature,leading to less electricity production capacity.This paper proposes an algorithm to solve the wind farm layout optimization problem considering multi-angular(MA)wind direction with the aim of maximizing the total power generated on wind farms and minimizing the cost of installation.A twostage genetic algorithm(GA)equipped with complementary sampling and uniform crossover is used to evolve a MA layout that will yield optimal output regardless of the wind direction.In the first stage,the optimal wind turbine layouts for 8 different major wind directions were determined while the second stage allows each of the previously determined layouts to compete and inter-breed so as to evolve an optimal MA wind farm layout.The proposed MA wind farm layout is thereafter compared to other layouts whose turbines have focused site specific wind turbine orientation.The results reveal that the proposed wind farm layout improves wind power production capacity with minimum cost of installation compared to the layouts with site specific wind turbine layouts.This paper will find application at the planning stage of wind farm.展开更多
The existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations,resulting in poor sales impact and cust...The existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations,resulting in poor sales impact and customer satisfaction.For such shortcomings,in this paper,we propose a mathematical programming approach for shelf layout problems based on comprehensive related value.First,we introduce the concepts of related value considering both attention and relevancy;second,we give the concept of adjacent utility value and the freedom of placement,and further analyze the impact of the same commodity on surrounding commodities due to different placement positions;third,we establish a new comprehensive related value-based commodity layout optimization model(CRV-CL)and provide the solution steps integrating with a genetic algorithm.Finally,we analyze the characteristics of CRV-CL through a specific case.The simulation results indicate the overall relevancy after applying the CRV-CL model.展开更多
文摘The increase in bridge structure span and the complex stress characteristics directly affect the optimization of sensor placement,which in turn influences the data acquisition performance of the monitoring system.The key to the information acquisition of a bridge monitoring system is to obtain data that meets the health monitoring requirements of the bridge with a limited number of measurement points.To address this,a hybrid method based on multiple optimization criteria is proposed for optimal sensor placement(OSP).First,the minimum number of modes required for bridge monitoring is determined using the information entropy criterion(IE).Then,the number of measurement points is determined using a sequence method combined with the modal assurance criterion(MAC).Finally,the sensor placement is optimized using the generalized genetic algorithm(GGA)combined with double-structure encoding,and the optimization results are validated through finite element model analysis.The research results show that the hybrid method based on multiple optimization criteria can effectively determine the number of measurement points for bridge structures and optimize sensor placement,with a significant improvement in computational speed.
基金Supported by School of Engineering, Napier University, United Kingdom, and partially supported by the National Natural Science Foundation of China (No.60273093).
文摘Genetic Algorithm (GA) is a biologically inspired technique and widely used to solve numerous combinational optimization problems. It works on a population of individuals, not just one single solution. As a result, it avoids converging to the local optimum. However, it takes too much CPU time in the late process of GA. On the other hand, in the late process Simulated Annealing (SA) converges faster than GA but it is easily trapped to local optimum. In this letter, a useful method that unifies GA and SA is introduced, which utilizes the advantage of the global search ability of GA and fast convergence of SA. The experimental results show that the proposed algorithm outperforms GA in terms of CPU time without degradation of performance. It also achieves highly comparable placement cost compared to the state-of-the-art results obtained by Versatile Place and Route (VPR) Tool.
基金Defense Science and Technology Pre- re-search Foundation Project!under Con-tract98J2 .5.8.JW0 30 1
文摘In order for optical interconnection technologies to be incorporated into the next generation parallel computers, new optoelectronic computer aided design, integration, and packaging technologies must be investigated. One of the key issues in designing is the system volume, which is determined by maximum interconnection distance(MID) between PEs. A novel 2 D genetic algorithm was presented in this paper at the first time, and used to solve the placement of twin butterfly multistage networks based on transmissive physical model. The experiment result shows that this algorithm case works better than other algorithm cases.
基金supported by State Grid Science and Technology Projects(SGTYHT/17-JS-199)National Natural Science Foundation of China(51577163).
文摘The fault current limiter(FCL)is an effective measure for improving system stability and suppressing short-circuit fault current.Because of space and economic costs,the optimum placement of FCLs is vital in industrial applications.In this study,two objectives with the same dimensional measurement unit,namely,the total capital investment cost of FCLs and circuit breaker loss related to short-circuit currents,are considered.The circuit breaker loss model is developed based on the attenuation rule of the circuit breaker service life.The circuit breaker loss is used to quantify the current-limiting effect to avoid the problem of weight selection in a multi-objective problem.The IEEE 10-generator 39-bus system in New England is used to evaluate the performance of the proposed genetic algorithm(GA)method.Comparative and sensitivity analyses are performed.The results of the optimized plan are validated through simulations,indicating the significant potential of the GA for such optimization.
文摘This study considers several computational techniques for solving one formulation of the wells placement problem (WPP). Usually the wells placement problem is tackled through the combined efforts of many teams using conventional approaches, which include gathering seismic data, conducting real-time surveys, and performing production interpretations in order to define the sweet spots. This work considers one formulation of the wells placement problem in heterogeneous reservoirs with constraints on inter-well spacing. The performance of three different types of algorithms for optimizing the well placement problem is compared. These three techniques are: genetic algorithm, simulated annealing, and mixed integer programming (IP). Example case studies show that integer programming is the best approach in terms of reaching the global optimum. However, in many cases, the other approaches can often reach a close to optimal solution with much more computational efficiency.
文摘With the development of Computerized Business Application, the amount of data is increasing exponentially. Cloud computing provides high performance computing resources and mass storage resources for massive data processing. In distributed cloud computing systems, data intensive computing can lead to data scheduling between data centers. Reasonable data placement can reduce data scheduling between the data centers effectively, and improve the data acquisition efficiency of users. In this paper, the mathematical model of data scheduling between data centers is built. By means of the global optimization ability of the genetic algorithm, generational evolution produces better approximate solution, and gets the best approximation of the data placement at last. The experimental results show that genetic algorithm can effectively work out the approximate optimal data placement, and minimize data scheduling between data centers.
文摘This paper presents a study for finding a solution to the placement of territorial resources for multipurpose wireless services considering also the restrictions imposed by the orography of the territory itself. To solve this problem genetic algorithms are used to identify sites where to place the resources for the optimal coverage of a given area. The used algorithm has demonstrated to be able to find optimal solutions in a variety of considered situations.
文摘Presents the study on the optimum location of actuators/sensors for active vibration control in aerospace flexible structures with the performance function first built by maximization of dissipation energy due to control action and a real coded genetic algorithm then proposed to produce a global optimum solution, and proves the feasibility and advantages of this algorithm with the example of a standard test function and a two collocated actuators/sensors cantilever, and comparing the results with those given in the literatures.
文摘This paper presents the design of stability augmentation system (SAS) for the airship, which is robust with respect to parametric plant uncertainties. A robust pole placement approach is adopted in the design, which uses genetic algorithm (GA) as the optimization tool to derive the most robust solution of the state-feedback gain matrix K. The method can guarantee the resulting closed-loop poles to remain in a specified allocation region despite plant parameter uncertainty. Thus, the longitudinal stability of the airship is augmented by robustly assigning the closed-loop poles in a prescribed region of the left half s-plane.
基金supported by Consejo Nacional de Humanidades,Ciencia y Tecnología(CONAHCYT)—México(No.863547)the fellowship 2021-000001-01NACF-00604 given to the G.H.Valencia-Riverathe scholarships 175599,64698,253652,and 296574,given to G.Tapia-Tinoco,A.Garcia-Perez,D.Granados-Lieberman,and M.Valtierra-Rodriguez,respectively,through the Sistema Nacional de Investigadoras e Investigadores(SNII)-CONAHCYT-México.
文摘A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes.The power rating of the ES is adjusted on the basis of the available active power at the bus.And in the optimization problem,it is expressed as the power ratio of the noncritical load(NCL)and critical load(CL).The implemented ES model is flexible,which can be used on any bus and any phase.The model determines the output voltage from the parameters and operating conditions at the point of common coupling(PCC).These conditions are integrated using the backward/forward sweep method(BFSM)and are updated during power flow calculations.The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BFSM-based genetic algorithm,which computes power flow and ES placement simultaneously.The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.
基金Supported by the State of Saxony Anhalt and Siemens AG(No.2577A/0027B)in Germany
文摘This paper presents a novel genetic algorithm for analog module placement based on a generalization of the two-dimensional bin packing problem. The genetic encoding and operators assure that all problem constraints are always satisfied. Thus the potential problems of adding penalty terms to the cost function are eliminated so that the search configuration space is drastically decreased. The dedicated cost function is based on the special requirements of analog integrated circuits. A fractional factorial experiment was conducted using an orthogonal array to study the algorithm parameters. A meta-GA was applied to determine the optimal parameter values. The algorithm was tested with several local benchmark circuits. The experimental results show that the algorithm has better performance than the simulated annealing approach with satisfactory results comparable to manual placement. This study demonstrates the effectiveness of the genetic algorithm in the analog module placement problem. The algorithm has been successfully used in a layout synthesis tool.
文摘Most wind turbines within wind farms are set up to face a pre-determined wind direction.However,wind directions are intermittent in nature,leading to less electricity production capacity.This paper proposes an algorithm to solve the wind farm layout optimization problem considering multi-angular(MA)wind direction with the aim of maximizing the total power generated on wind farms and minimizing the cost of installation.A twostage genetic algorithm(GA)equipped with complementary sampling and uniform crossover is used to evolve a MA layout that will yield optimal output regardless of the wind direction.In the first stage,the optimal wind turbine layouts for 8 different major wind directions were determined while the second stage allows each of the previously determined layouts to compete and inter-breed so as to evolve an optimal MA wind farm layout.The proposed MA wind farm layout is thereafter compared to other layouts whose turbines have focused site specific wind turbine orientation.The results reveal that the proposed wind farm layout improves wind power production capacity with minimum cost of installation compared to the layouts with site specific wind turbine layouts.This paper will find application at the planning stage of wind farm.
文摘The existing shelf layout methods do not explicitly consider the attention and relevancy of the commodity systematically and thus have failed to capture the invalid associations,resulting in poor sales impact and customer satisfaction.For such shortcomings,in this paper,we propose a mathematical programming approach for shelf layout problems based on comprehensive related value.First,we introduce the concepts of related value considering both attention and relevancy;second,we give the concept of adjacent utility value and the freedom of placement,and further analyze the impact of the same commodity on surrounding commodities due to different placement positions;third,we establish a new comprehensive related value-based commodity layout optimization model(CRV-CL)and provide the solution steps integrating with a genetic algorithm.Finally,we analyze the characteristics of CRV-CL through a specific case.The simulation results indicate the overall relevancy after applying the CRV-CL model.
